Skill UI

A comprehensive pre-submission strategy guide designed to 'red-team' theoretical and econometric manuscripts. This tool helps authors anticipate and pre-empt harsh critiques from expert co-editors and referees, focusing specifically on identifying proof gaps, testing the generality of claims, ensuring finite-sample evidence, and addressing potential methodological competitors before journal submission.

This guide details the requirements for creating a comprehensive replication package for manuscripts submitted to Econometric Society journals. It ensures full reproducibility of all results, including code, data provenance, and parameter settings, adhering to the journal's Data and Code Availability Policy. Key components include a master script, reproducible data, and detailed documentation.

A comprehensive preflight checklist for authors submitting manuscripts to Econometrica. It details strict guidelines on manuscript length (main body and supplemental material), formatting, anonymization protocols, membership requirements, and adhering to the latest Data and Code Availability Policy. Use this guide before submission to ensure full compliance with the journal's standards.

A comprehensive guide for structuring, auditing, and writing mathematically rigorous proofs for advanced academic papers, particularly in econometrics and statistics. It covers everything from defining assumptions and stating self-contained theorems to applying advanced proof techniques (e.g., fixed-point theorems, CLT). Use this when your central result requires impeccable rigor and completeness for top-tier publication.

This tool helps researchers diagnose whether their empirical or theoretical result meets the high standards required for top-tier academic journals like Econometrica. It guides users to evaluate the generality, methodological novelty, and theoretical depth of their work, ensuring the contribution is a generalizable estimator or theorem, not merely an application.

This guide details the principles of conducting rigorous Monte Carlo simulations for econometric theory papers. It instructs users on designing simulations that test finite-sample behavior, ensuring that asymptotic approximations are useful and accurate across boundary cases (e.g., weak identification, heavy tails). Emphasis is placed on reproducibility, comprehensive metrics (bias, coverage, power), and ensuring the simulation supports the core theory.

This guide offers a rigorous framework for structuring advanced econometric theory papers. It details how to move beyond simple identification by defining minimal, defensible assumptions, proving advanced limit theorems (e.g., FCLT, high-dimensional limits), and ensuring the result's generality across various data regimes (stationary, nonstationary, semiparametric). Use this when theoretical rigor is the primary challenge.

This skill guides researchers on how to position a new econometric theorem by rigorously comparing it against the existing theoretical literature frontier. Instead of a general survey, it requires defining the 'delta'—the specific element (e.g., weaker assumptions, broader scope, generalization) that distinguishes the new result from prior work, using formal APA author-date citations. Essential for high-level academic manuscripts.

This guide helps authors prepare for high-level theoretical journal submissions, focusing on the specific requirements of single-anonymous peer review. It details appropriate article types (Article, Miscellanea, ET Interviews), and provides a comprehensive checklist to war-game potential referee objections regarding assumptions, proof gaps, convergence rates, and novelty, significantly improving submission quality.

This comprehensive checklist guides researchers through the detailed formatting and technical requirements for submitting manuscripts to the Econometric Theory journal via ScholarOne/Manuscript Central. It covers critical points such as creating a single embedded-font PDF, adhering to APA author-date referencing, maintaining single-anonymous identity, and managing the article length ceiling (50 pages). Use this before final submission to avoid common rejection reasons.

This guide helps researchers determine if their econometric result is a general, foundational theory contribution (such as asymptotics or proofs) or merely an applied estimate. It provides a framework for assessing theoretical rigor, identifying generalizations, and deciding whether the work fits a full Article or a concise Miscellanea, ensuring proper submission targeting for top-tier journals.

This guide provides comprehensive standards for conducting and reporting rigorous empirical and simulation evidence in econometrics. It covers designing Monte Carlo simulations, creating minimum evidence maps, ensuring reproducibility through detailed logging, and linking theoretical claims directly to finite-sample evidence. Essential for high-level statistical research.